Masashi Kitamura

83 papers receiving 685 citations

Peers

Masashi Kitamura
Comparison fields: 5 of 121
  • Cell Biology 101
  • Electronic, Optical and Magnetic Materials 87
  • Physiology 21
  • Toxicology 11
  • Pharmacology 27
Replace In-Seon Kim with:
In-Seon Kim South Korea
Yunge Li China
Yingjie Sun China
Chia-Wei Chang Taiwan
Weiwei Zhang China
Mojtaba Ranjbar Iran
Mingxu Hu United States
Michael Bartsch United States
Praveen K. Shukla India
Takashi Iwasa Japan
Masashi Kitamura relative to In-Seon Kim South Korea In-Seon Kim's profile →
Citations per field
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Citations per year

Countries citing papers authored by Masashi Kitamura

Since Specialization
Citations

This map shows the geographic impact of Masashi Kitamura's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Masashi Kitamura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masashi Kitamura more than expected).

Fields of papers citing papers by Masashi Kitamura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Masashi Kitamura. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Masashi Kitamura. The network helps show where Masashi Kitamura may publish in the future.

Co-authors

The 25 scholars most cited alongside Masashi Kitamura, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Masashi Kitamura Line = papers co-authored together Masashi Kitamura links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200558
2 200334
3 200333
4 200933
5 202326
6 202122
7 202022
8 201621
9 200518
10 201718
11 200417
12 199917
13 202215
14 202215
15 201215
16 200415
17 201914
18 201814
19 199414
20 201614

About Masashi Kitamura

Masashi Kitamura is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Electronic, Optical and Magnetic Materials, Molecular Biology and Control and Systems Engineering, having authored 90 papers that have together received 700 indexed citations. Recurring topics across this work include Electric Motor Design and Analysis (21 papers), Superconducting Materials and Applications (15 papers), Magnetic Properties and Applications (14 papers), Magnetic Bearings and Levitation Dynamics (8 papers), Biosensors and Analytical Detection (7 papers), Magnetic Properties of Alloys (5 papers), Advanced MRI Techniques and Applications (5 papers) and Advanced NMR Techniques and Applications (5 papers). The work is most often cited by research in Cell Biology (101 citations), Electronic, Optical and Magnetic Materials (87 citations), Physiology (21 citations), Toxicology (11 citations) and Pharmacology (27 citations). Masashi Kitamura has collaborated with scholars based in Japan, United States and India. Frequent co-authors include Yûji Enomoto, Kazuhisa Nakayama, Ryuichiro Suzuki, Hye‐Won Shin, Takashi Tanikawa, Yohei Sasaki, Yutaka Inoue, M. Komuro, Kazuhito Watanabe and Atsushi Asano. Their work appears in journals such as IEEE Transactions on Magnetics, IEEJ Transactions on Industry Applications, Journal of Natural Medicines, Journal of Nuclear Science and Technology and IEEE Transactions on Applied Superconductivity.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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